Soil Erosion Assessment Using the RUSLE Model, Remote Sensing, and GIS in the Shatt Al-Arab Basin (Iraq-Iran)
Source abstract
Abstract
In the Shatt Al-Arab basin, soil erosion is a major problem due to the steepness of the terrain and the significant difference in altitude between the upstream and downstream parts of the basin. Vast quantities of soil are moved annually, resulting in massive repercussions including soil degradation, structural damage, biodiversity loss, and productivity reduction in the catchment area, huge sediment load, and the pollution of streams and rivers. Consequently, the assessment of soil erosion risk and geographical distribution is essential for constructing a database for developing effective control strategies. Revised Universal Soil Loss Equation (RUSLE) was combined with Remote Sensing (RS) and Geographic Information System (GIS) in the current work to define the soil erosion hazard map in the Shatt Al-Arab basin. The RUSLE model included various characteristics for soil erosion zonation including rainfall erosivity, soil erodibility, slope length and steepness, land cover and management, and conservation support practices. Annual erosion rates in this study in tons per hectare were: extremely high (more than 50); very high (50 to 16.5); high (16.5 to 2.2); medium (2.2 to 1); and low (1 to 0) ton ha−1year−1 representing 16, 4, 13, 7, and 60 % of the basin’s area, respectively. The high soil loss rates are associated with heavy rainfall, loamy soil predominance, elevated terrains/plateau borders with a steep side slope, and intensive farming. Managers and policymakers may use the results of this study to implement adequate conservation programs to prevent soil erosion or recommend soil conservation acts if development projects are to proceed in places with a high soil erosion risk.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Soil erosion and sediment transport · Aeolian processes and effects · Groundwater and Watershed Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Geography, Philipps-University of Marburg, Deutschhausstr. 10, 35037 Marburg, Germany
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